gamedevlop

gunship999

AI & ML interests

None yet

Recent Activity

reacted to openfree's post with โž• about 1 month ago
๐Ÿš€ Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft! https://huggingface.co/spaces/VIDraft/phi-4-reasoning-plus ๐ŸŒŸ Key Highlights Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance. Extended Context (32k tokens): Capable of handling lengthy and complex input sequences. Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges. Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries. ๐Ÿ… Benchmark Achievements Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models: Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%). Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%. Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning. Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models. ๐Ÿ›ก๏ธ Safety and Robustness Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments. High standards of alignment and responsible AI compliance validated through extensive adversarial testing. ๐ŸŽฏ Recommended Applications Phi-4-reasoning-plus is especially suitable for: Systems with limited computational resources. Latency-sensitive applications requiring quick yet accurate responses. ๐Ÿ“œ License Freely available under the MIT License for broad accessibility and flexible integration into your projects.
reacted to openfree's post with ๐Ÿ˜Ž about 1 month ago
๐Ÿš€ Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft! https://huggingface.co/spaces/VIDraft/phi-4-reasoning-plus ๐ŸŒŸ Key Highlights Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance. Extended Context (32k tokens): Capable of handling lengthy and complex input sequences. Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges. Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries. ๐Ÿ… Benchmark Achievements Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models: Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%). Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%. Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning. Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models. ๐Ÿ›ก๏ธ Safety and Robustness Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments. High standards of alignment and responsible AI compliance validated through extensive adversarial testing. ๐ŸŽฏ Recommended Applications Phi-4-reasoning-plus is especially suitable for: Systems with limited computational resources. Latency-sensitive applications requiring quick yet accurate responses. ๐Ÿ“œ License Freely available under the MIT License for broad accessibility and flexible integration into your projects.
reacted to openfree's post with ๐Ÿค— about 1 month ago
๐Ÿš€ Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft! https://huggingface.co/spaces/VIDraft/phi-4-reasoning-plus ๐ŸŒŸ Key Highlights Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance. Extended Context (32k tokens): Capable of handling lengthy and complex input sequences. Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges. Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries. ๐Ÿ… Benchmark Achievements Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models: Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%). Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%. Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning. Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models. ๐Ÿ›ก๏ธ Safety and Robustness Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments. High standards of alignment and responsible AI compliance validated through extensive adversarial testing. ๐ŸŽฏ Recommended Applications Phi-4-reasoning-plus is especially suitable for: Systems with limited computational resources. Latency-sensitive applications requiring quick yet accurate responses. ๐Ÿ“œ License Freely available under the MIT License for broad accessibility and flexible integration into your projects.
View all activity

Organizations

VIDraft's profile picture PowergenAI's profile picture

gunship999's activity

reacted to openfree's post with โž•๐Ÿ˜Ž๐Ÿค—โค๏ธ๐Ÿ‘€๐Ÿš€๐Ÿ”ฅ about 1 month ago
view post
Post
2806
๐Ÿš€ Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft!

VIDraft/phi-4-reasoning-plus

๐ŸŒŸ Key Highlights
Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance.

Extended Context (32k tokens): Capable of handling lengthy and complex input sequences.

Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges.

Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries.

๐Ÿ… Benchmark Achievements
Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models:

Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%).

Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%.

Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning.

Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models.

๐Ÿ›ก๏ธ Safety and Robustness
Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments.

High standards of alignment and responsible AI compliance validated through extensive adversarial testing.

๐ŸŽฏ Recommended Applications
Phi-4-reasoning-plus is especially suitable for:
Systems with limited computational resources.
Latency-sensitive applications requiring quick yet accurate responses.

๐Ÿ“œ License
Freely available under the MIT License for broad accessibility and flexible integration into your projects.
  • 2 replies
ยท
reacted to ginipick's post with ๐Ÿ‘€๐Ÿš€๐Ÿ”ฅ about 2 months ago
view post
Post
3945
๐Ÿš€ AI Blog Generator with Streamlit: The Ultimate Guide!

ginigen/blogger

Hello there! Today I'm excited to introduce you to a powerful AI blog creation tool called Ginigen Blog. This amazing app automatically generates high-quality blog content using Streamlit and the latest ChatGPT 4.1 API. And the best part? It's completely free to use! ๐Ÿ‘ฉโ€๐Ÿ’ปโœจ

๐Ÿง  What Makes Ginigen Blog Special
Ginigen Blog is not just a simple text generator! It offers these exceptional features:

Multiple Blog Templates: SEO-optimized, tutorials, reviews, and more
Web Search Integration: Creates accurate content based on the latest information
File Upload Analysis: Automatically analyzes TXT, CSV, and PDF files to incorporate into blogs
Automatic Image Generation: Creates images that match your blog topic
Various Output Formats: Download in Markdown, HTML, and more
Latest GPT-4.1 Model: Cutting-edge AI technology for higher quality blog creation
Completely Free Service: Access high-quality content generation without any cost!

๐Ÿ’ช Who Is This Tool For?

๐Ÿ“ Content marketers and bloggers
๐Ÿข Corporate blog managers
๐Ÿ‘จโ€๐Ÿซ Educational content creators
๐Ÿ›๏ธ Product reviewers
โœ๏ธ Anyone looking to save time on writing!

๐Ÿ› ๏ธ How Does It Work?
Ginigen Blog generates high-quality blogs with just a simple topic input:

Enter a Blog Topic: Input your desired topic or keywords
Select Settings: Choose template, tone, word count, etc.
Utilize Web Search: Automatically incorporates the latest information into your blog
Upload Files: Upload reference files if needed
Auto-Generate: The AI analyzes all information to create a complete blog post
Download: Get your content immediately in Markdown or HTML format!

๐ŸŒŸ Use Cases
๐ŸŽญ "Summer festivals in 2025: A comprehensive guide to major regional events and hidden attractions"

๐Ÿ’Œ Closing Thoughts
Ginigen Blog is a powerful tool that significantly reduces content creation time while maintaining quality.
replied to aiqtech's post about 2 months ago
view reply

Open source keeps the gates of knowledge wide open for everyone. Enhancing this code and sharing it back with the community is one of the noblest acts in the digital ageโ€”the beating heart of a technological ecosystem where we grow together.

Great!

reacted to aiqtech's post with ๐Ÿ”ฅ about 2 months ago
view post
Post
4560
๐ŸŒ AI Token Visualization Tool with Perfect Multilingual Support

Hello! Today I'm introducing my Token Visualization Tool with comprehensive multilingual support. This web-based application allows you to see how various Large Language Models (LLMs) tokenize text.

aiqtech/LLM-Token-Visual

โœจ Key Features

๐Ÿค– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
๐Ÿ”„ Custom Model Support: Use any tokenizer available on HuggingFace
๐Ÿ“Š Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more
๐ŸŒˆ Visual Token Representation: Each token assigned a unique color for visual distinction
๐Ÿ“‚ File Analysis Support: Upload and analyze large files

๐ŸŒ Powerful Multilingual Support
The most significant advantage of this tool is its perfect support for all languages:

๐Ÿ“ Asian languages including Korean, Chinese, and Japanese fully supported
๐Ÿ”ค RTL (right-to-left) languages like Arabic and Hebrew supported
๐Ÿˆบ Special characters and emoji tokenization visualization
๐Ÿงฉ Compare tokenization differences between languages
๐Ÿ’ฌ Mixed multilingual text processing analysis

๐Ÿš€ How It Works

Select your desired tokenizer model (predefined or HuggingFace model ID)
Input multilingual text or upload a file for analysis
Click 'Analyze Text' to see the tokenized results
Visually understand how the model breaks down various languages with color-coded tokens

๐Ÿ’ก Benefits of Multilingual Processing
Understanding multilingual text tokenization patterns helps you:

Optimize prompts that mix multiple languages
Compare token efficiency across languages (e.g., English vs. Korean vs. Chinese token usage)
Predict token usage for internationalization (i18n) applications
Optimize costs for multilingual AI services

๐Ÿ› ๏ธ Technology Stack

Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: ๐Ÿค— Transformers library
ยท
reacted to fantos's post with ๐Ÿ”ฅ about 2 months ago
view post
Post
4288
๐ŸŽจ BadgeCraft: Create Beautiful Badges with Ease! โœจ
Hello there! Today I'm introducing BadgeCraft, a simple app that lets you create stunning badges for your websites, GitHub READMEs, and documentation.

๐ŸŒŸ Key Features

๐Ÿ–Œ๏ธ 14 diverse color options including vibrant neon colors
๐Ÿ”ค Custom text input for label and message
๐Ÿ–ผ๏ธ Support for 2000+ logos via Simple Icons
๐Ÿ”— Clickable link integration
๐Ÿ‘๏ธ Real-time preview
๐Ÿ’ป Ready-to-use HTML code generation

๐Ÿ“ How to Use

Label - Enter the text to display on the left side of the badge (e.g., "Discord", "Version", "Status")
Message - Enter the text to display on the right side of the badge
Logo - Type the name of a logo provided by Simple Icons (e.g., "discord", "github")
Style - Choose the shape of your badge (flat, plastic, for-the-badge, etc.)
Color Settings - Select background color, label background color, and logo color
Link - Enter the URL that the badge will link to when clicked

โœ… Use Cases

Add social media links to your GitHub project README
Display version information or download links on your website
Include tech stack badges in blog posts
Show status indicators in documentation (e.g., "in development", "stable")

๐Ÿ’ก Tips

Click on any of the prepared examples to automatically fill in all settings
Copy the generated HTML code and paste directly into your website or blog
HTML works in GitHub READMEs, but if you prefer markdown, use the ![alt text](badge URL) format

๐Ÿ‘จโ€๐Ÿ’ป Tech Stack
This app was built using Gradio and leverages the shields.io API to generate badges. Its simple UI makes it accessible for everyone!

๐Ÿ”— openfree/Badge

โœจ Available under MIT License - feel free to use and modify.
  • 1 reply
ยท
reacted to openfree's post with โค๏ธ๐Ÿค—๐Ÿ˜Žโž•๐Ÿง ๐Ÿ‘๐Ÿค about 2 months ago
view post
Post
4577
๐Ÿ“Š Papers Impact: Instant AI Grading for Your Research Papers! ๐Ÿš€

๐ŸŒŸ Introduction
Hello, AI research community! ๐ŸŽ‰
Introducing Papers Impact - the revolutionary AI tool that automatically grades and predicts the potential impact of research papers! ๐Ÿง ๐Ÿ’ก

VIDraft/PapersImpact

โœจ Key Feature: Instant Paper Grading
The core functionality is brilliantly simple: Just enter an arXiv paper ID or URL, and our AI instantly analyzes and grades the paper's potential academic impact! No need to read through the entire paper yourself - our system automatically evaluates the title and abstract to generate a normalized impact score between 0 and 1.
๐ŸŽฏ How It Works

Enter Paper ID or URL: Simply paste an arXiv ID (e.g., "2504.11651") or full URL
Automatic Fetching: The system retrieves the paper's title and abstract
AI Analysis: Our advanced LLaMA-based transformer model analyzes the content
Instant Grading: Receive an impact score and corresponding letter grade in seconds!

๐Ÿ’ก Who Can Benefit?

๐Ÿ”ฌ Researchers: Pre-assess your paper before submission
๐Ÿ“š Students: Quickly gauge the quality of papers for literature reviews
๐Ÿซ Educators: Objectively evaluate student research
๐Ÿ“Š Research Managers: Prioritize which papers to read in depth
๐Ÿงฉ Journal Editors: Get an AI second opinion on submissions

๐Ÿš€ Technical Details
Our model is trained on an extensive dataset of published papers in CS.CV, CS.CL, and CS.AI fields, using NDCG optimization with Sigmoid activation and MSE loss. It's been rigorously cross-validated against historical citation data to ensure accurate impact predictions.
  • 2 replies
ยท